proJ#1 (Saladar)
BRYCE KENDRIC SALADAR
2022-12-03
library("syuzhet")## Warning: package 'syuzhet' was built under R version 4.2.2library("wordcloud")## Warning: package 'wordcloud' was built under R version 4.2.2## Loading required package: RColorBrewerlibrary("plotly")## Warning: package 'plotly' was built under R version 4.2.2## Loading required package: ggplot2## Warning: package 'ggplot2' was built under R version 4.2.2##
## Attaching package: 'plotly'## The following object is masked from 'package:ggplot2':
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## last_plot## The following object is masked from 'package:stats':
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## filter## The following object is masked from 'package:graphics':
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## layoutlibrary("tm")## Warning: package 'tm' was built under R version 4.2.2## Loading required package: NLP##
## Attaching package: 'NLP'## The following object is masked from 'package:ggplot2':
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## annotatelibrary("tidytext")## Warning: package 'tidytext' was built under R version 4.2.2library("dplyr")## Warning: package 'dplyr' was built under R version 4.2.2##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
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## filter, lag## The following objects are masked from 'package:base':
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## intersect, setdiff, setequal, unionlibrary("RColorBrewer")
library("ggplot2")
library("magrittr")
library("stringr")## Warning: package 'stringr' was built under R version 4.2.2library("twitteR")## Warning: package 'twitteR' was built under R version 4.2.2##
## Attaching package: 'twitteR'## The following objects are masked from 'package:dplyr':
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## id, locationCONSUMER_SECRET <- "c4lW91jDaRUgzFAvOr0YleNYVEm17ZTnEHnMsvlDcjKSJnBJXg"
CONSUMER_KEY <- "pgjt5UWX2uzuK6qRwHowEPPXq"
ACCESS_SECRET <- "txachtOgZ7L0dyj9vAswZkfGjtJMfU4fVvRdAyEo3jNg0"
ACCESS_TOKEN <- "1594899110103986176-QoH3VZuNGyLd8RBuY6cnFR4lN6obA4"
setup_twitter_oauth(consumer_key = CONSUMER_KEY,
consumer_secret = CONSUMER_SECRET,
access_token = ACCESS_TOKEN,
access_secret = ACCESS_SECRET)## [1] "Using direct authentication"trendTweets <- searchTwitter("#China -filter:retweets", n=10000, lang="en", since="2022-11-26", until="2022-12-2",
retryOnRateLimit = 120)
trendTweetsDF <- twListToDF(trendTweets)
class(trendTweetsDF)## [1] "data.frame"names(trendTweetsDF)## [1] "text" "favorited" "favoriteCount" "replyToSN"
## [5] "created" "truncated" "replyToSID" "id"
## [9] "replyToUID" "statusSource" "screenName" "retweetCount"
## [13] "isRetweet" "retweeted" "longitude" "latitude"View(trendTweetsDF)
head(trendTweetsDF)[1:5]head(trendTweetsDF$text)[1:5]## [1] "#Bitcoin #USA #King #International Bitcoin\n#Congo #England #Kenya #China #Siam #Portugal El Salvador #Italy #Brazil… https://t.co/9OCnrHl47V"
## [2] "@KINGDADADA4 @realdogen @GreenXmasERC #RabbitInu probably the best meme coin 2023 #RINU #China https://t.co/KKeBjneAw3"
## [3] "Deputy Minister Tsai gave an interview to @TVPWorld_com’s @FilipStyczynski. He detailed #Taiwan’s🇹🇼 strengthening o… https://t.co/jhKXeORp3y"
## [4] "Reasonable analysis of current Events in #China.\n\n#ChinaProtests https://t.co/QSDDNoafD1"
## [5] "A video of an audio statement in Arabic titled:\nLet Whoever Hates Me Dig Their Own Grave.\n19- Rabi Than-1444AH \n13-… https://t.co/b5gxKc8cZV"save(trendTweetsDF,file = "trendingTweetsDF.Rdata")
load(file = "trendingTweetsDF.Rdata")
tweetsDF1 <- trendTweetsDF %>%
select(screenName, text, created, statusSource)
save(tweetsDF1, file = "tweetsDF.Rdata")#Checking missing values
nien <- sapply(trendTweetsDF, function(x) sum(is.na(x)))
nien## text favorited favoriteCount replyToSN created
## 0 0 0 8624 0
## truncated replyToSID id replyToUID statusSource
## 0 8782 0 8624 0
## screenName retweetCount isRetweet retweeted longitude
## 0 0 0 0 9956
## latitude
## 9956#Subsetting dyplr
tweetsDF0 <- trendTweetsDF %>%
select(screenName,text,created,statusSource)
tweetsDF0#Assembling the data created
tweetsDF0 %>%
group_by(1) %>%
summarise(max = max(created), min = min(created))reviour <- tweetsDF1 %>% mutate(Created_At_Round = created %>% round(units = 'hours') %>% as.POSIXct())
reviourtweetsDF0 %>% pull(created) %>% min() ## [1] "2022-11-30 04:54:57 UTC"tweetsDF0 %>% pull(created) %>% max()## [1] "2022-12-01 23:59:57 UTC"#Arranging the plot usuing plotly and ggplot
ggplot(data = tweetsDF1, aes(x = created)) +
geom_histogram(aes(fill = ..count..)) +
theme(legend.position = "upper right") +
xlab("Time") + ylab("Number of tweets") +
scale_fill_gradient(low = "grey",high = "blue")## Warning: The dot-dot notation (`..count..`) was deprecated in ggplot2 3.4.0.
## ℹ Please use `after_stat(count)` instead.## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
#Plotting
Sourceplotss <- function(x) {
if(grepl(">Twitter for iPhone</a>", x)){
"iphone"
}else if(grepl(">Twitter for iPad</a>", x)){
"ipad"
}else if(grepl(">Twitter for Android</a>", x)){
"android"
} else if(grepl(">Twitter Web Client</a>", x)){
"Web"
} else if(grepl(">Twitter for Windows Phone</a>", x)){
"windows phone"
}else if(grepl(">dlvr.it</a>", x)){
"dlvr.it"
}else if(grepl(">IFTTT</a>", x)){
"ifttt"
}else if(grepl(">Facebook</a>", x)){
"facebook"
}else {
"others"
}
}
tweetsDF0$tweetSource = sapply(tweetsDF0$statusSource,Sourceplotss)
tweetplotts <- tweetsDF0 %>%
select(tweetSource) %>%
group_by(tweetSource) %>%
summarize(count=n()) %>%
arrange(desc(count))
ggplot(tweetsDF0[tweetsDF0$tweetSource != 'others',], aes(tweetSource, fill = tweetSource)) +
geom_bar() +
theme(legend.position="none",
axis.title.x = element_blank(),
axis.text.x = element_text(angle = 45, hjust = 1)) +
ylab("Number of tweets") +
ggtitle("Tweets by Source")
#Accounts that Tweets about China
tweetplotss <- tweetsDF0 %>%
select(screenName) %>%
group_by(screenName) %>%
summarize(count=n()) %>%
arrange(desc(count)) #CORPUS
corpse <- Corpus(VectorSource(tweetsDF1$screenName))
class(tweetsDF1$screenName)## [1] "character"oiu <- class(VectorSource(tweetsDF1$screenName))
oiu## [1] "VectorSource" "SimpleSource" "Source"str(corpse)## Classes 'SimpleCorpus', 'Corpus' hidden list of 3
## $ content: chr [1:10000] "JamesWe42087922" "PigeArmy888" "MOFA_Taiwan" "neferimhotep" ...
## $ meta :List of 1
## ..$ language: chr "en"
## ..- attr(*, "class")= chr "CorpusMeta"
## $ dmeta :'data.frame': 10000 obs. of 0 variablesclass(corpse)## [1] "SimpleCorpus" "Corpus"kin <- corpse
kin## <<SimpleCorpus>>
## Metadata: corpus specific: 1, document level (indexed): 0
## Content: documents: 10000WORDCLOUD FOR SCREEN_NAMES.
cloud <- brewer.pal(8, "Dark2")
clouds <- cloud[-(1:4)]
set.seed(123)
par(mar = c(0,0,0,0), mfrow = c(1,1))
wordcloud(words = corpse, scale=c(3,0.5),
max.words=500,
random.order=FALSE,
rot.per=0.5,
use.r.layout=TRUE,
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